This files contains an example of tuning a multiple models with BayesSearchCV.

import pickle
import time

import helpsk as hlp
import pandas as pd
import numpy as np
import plotly.express as px
from sklearn.impute import SimpleImputer
from sklearn.pipeline import Pipeline
from sklearn.preprocessing import StandardScaler, MinMaxScaler, OneHotEncoder

import plotly.io as pio
pio.renderers.default='notebook'

Load Data

with open('../X_train.pkl', 'rb') as handle:
    X_train = pickle.load(handle)

with open('../y_train.pkl', 'rb') as handle:
    y_train = pickle.load(handle)

hlp.pandas.numeric_summary(X_train, return_style=True)

	# of Non-Nulls	# of Nulls	% Nulls	# of Zeros	% Zeros	Mean	St Dev.	Coef of Var	Skewness	Kurtosis	Min	10%	25%	50%	75%	90%	Max
duration	760	40	5.0%	0	0.0%	21.0	11.7	0.6	1.0	0.6	4.0	9.0	12.0	18.0	24.0	36.0	60.0
credit_amount	800	0	0.0%	38	5.0%	3,203.9	2,932.3	0.9	1.9	3.9	0.0	753.9	1,300.8	2,236.5	3,951.5	7,394.6	18,424.0
installment_commitment	800	0	0.0%	0	0.0%	3.0	1.1	0.4	-0.5	-1.2	1.0	1.0	2.0	3.0	4.0	4.0	4.0
residence_since	800	0	0.0%	0	0.0%	2.9	1.1	0.4	-0.3	-1.4	1.0	1.0	2.0	3.0	4.0	4.0	4.0
age	800	0	0.0%	0	0.0%	35.6	11.4	0.3	1.0	0.7	19.0	23.0	27.0	33.0	42.0	52.0	75.0
existing_credits	800	0	0.0%	0	0.0%	1.4	0.6	0.4	1.3	1.6	1.0	1.0	1.0	1.0	2.0	2.0	4.0
num_dependents	800	0	0.0%	0	0.0%	1.1	0.3	0.3	2.0	2.1	1.0	1.0	1.0	1.0	1.0	2.0	2.0

hlp.pandas.non_numeric_summary(X_train, return_style=True)

	# of Non-Nulls	# of Nulls	% Nulls	Most Freq. Value	# of Unique	% Unique
checking_status	763	37	4.6%	no checking	4	0.5%
credit_history	800	0	0.0%	existing paid	5	0.6%
purpose	800	0	0.0%	radio/tv	10	1.2%
savings_status	800	0	0.0%	<100	5	0.6%
employment	800	0	0.0%	1<=X<4	5	0.6%
personal_status	800	0	0.0%	male single	4	0.5%
other_parties	800	0	0.0%	none	3	0.4%
property_magnitude	800	0	0.0%	car	4	0.5%
other_payment_plans	800	0	0.0%	none	3	0.4%
housing	800	0	0.0%	own	3	0.4%
job	800	0	0.0%	skilled	4	0.5%
own_telephone	800	0	0.0%	none	2	0.2%
foreign_worker	800	0	0.0%	yes	2	0.2%

y_train[0:10]

array([1, 1, 0, 1, 0, 1, 0, 1, 1, 0])

np.unique(y_train, return_counts=True)

(array([0, 1]), array([559, 241]))

np.unique(y_train, return_counts=True)[1] / np.sum(np.unique(y_train, return_counts=True)[1])

array([0.69875, 0.30125])

skopt.BayesSearchCV

https://scikit-optimize.github.io/stable/auto_examples/sklearn-gridsearchcv-replacement.html

search_space = hlp.sklearn_search.ClassifierSearchSpace(data=X_train)

# pip install scikit-optimize
from skopt import BayesSearchCV
from skopt.space import Real, Categorical, Integer
from sklearn.model_selection import RepeatedKFold

bayes_search = BayesSearchCV(
    estimator=search_space.pipeline(),
    search_spaces=search_space.search_spaces(),
    cv=RepeatedKFold(n_splits=5, n_repeats=2),  # 5 fold 2 repeat CV
    scoring='roc_auc',
    refit=False,  # required if passing in multiple scorers
    return_train_score=False,
    n_jobs=-1,
    verbose=1,
    random_state=42,
)

start_time = time.time()
bayes_search.fit(X_train, y_train)
elapsed_time = time.time() - start_time

print(f"Elapsed time to run BayesSearchCV: {elapsed_time:.3f} seconds; {elapsed_time / 60:.1f} minutes")

Elapsed time to run BayesSearchCV: 503.255 seconds; 8.4 minutes

print(bayes_search.best_score_)

0.7795560629842554

print(bayes_search.best_params_)

OrderedDict([('model', RandomForestClassifier(n_estimators=500)), ('model__criterion', 'gini'), ('model__max_depth', 100), ('model__max_features', 0.01), ('model__max_samples', 0.5), ('model__min_samples_leaf', 1), ('model__min_samples_split', 50), ('prep__non_numeric__encoder__transformer', OneHotEncoder(handle_unknown='ignore')), ('prep__numeric__imputer__transformer', SimpleImputer()), ('prep__numeric__scaler__transformer', None)])

Results

results = hlp.sklearn_eval.MLExperimentResults.from_sklearn_search_cv(
    searcher=bayes_search,
    higher_score_is_better=True,
    description='BayesSearchCV using ClassifierSearchSpace',
    parameter_name_mappings=search_space.param_name_mappings()
)

results.to_yaml_file(yaml_file_name = 'Run 1 - Multi-model - BayesSearchCV.yaml')

results = hlp.sklearn_eval.MLExperimentResults.from_yaml_file(yaml_file_name = 'Run 1 - Multi-model - BayesSearchCV.yaml')

Best Scores/Params

results.best_score

0.7795560629842554

results.best_params

{'model': 'RandomForestClassifier()',
 'max_features': 0.01,
 'max_depth': 100,
 'min_samples_split': 50,
 'min_samples_leaf': 1,
 'max_samples': 0.5,
 'criterion': 'gini',
 'imputer': 'SimpleImputer()',
 'scaler': 'None',
 'encoder': 'OneHotEncoder()'}

results.to_formatted_dataframe(return_style=True,
                               include_rank=True,
                               num_rows=1000)

rank	roc_auc Mean	roc_auc 95CI.LO	roc_auc 95CI.HI	model	max_features	max_depth	min_samples_split	min_samples_leaf	max_samples	criterion	C	learning_rate	n_estimators	min_child_weight	subsample	colsample_bytree	colsample_bylevel	reg_alpha	reg_lambda	imputer	scaler	encoder
1	0.780	0.755	0.804	RandomForestClassifier()	0.010	100.000	50.000	1.000	0.500	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	None	OneHotEncoder()
2	0.779	0.740	0.819	RandomForestClassifier()	0.091	100.000	50.000	5.000	0.500	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	None	OneHotEncoder()
3	0.779	0.762	0.796	RandomForestClassifier()	0.074	58.000	50.000	6.000	0.500	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	None	OneHotEncoder()
4	0.778	0.753	0.803	LinearSVC()	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	0.007	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	StandardScaler()	OneHotEncoder()
5	0.777	0.756	0.798	LogisticRegression()	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	0.101	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	StandardScaler()	OneHotEncoder()
6	0.776	0.742	0.810	RandomForestClassifier()	0.025	88.000	47.000	4.000	0.764	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	None	OneHotEncoder()
7	0.775	0.747	0.802	RandomForestClassifier()	0.010	84.000	50.000	1.000	0.500	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	None	OneHotEncoder()
8	0.774	0.753	0.795	RandomForestClassifier()	0.059	100.000	50.000	8.000	0.822	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='median')	None	OneHotEncoder()
9	0.774	0.761	0.787	LogisticRegression()	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	0.046	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	StandardScaler()	OneHotEncoder()
10	0.774	0.753	0.794	RandomForestClassifier()	0.141	67.000	50.000	1.000	0.570	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	None	CustomOrdinalEncoder()
11	0.773	0.744	0.802	RandomForestClassifier()	0.092	100.000	50.000	2.000	0.500	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	None	OneHotEncoder()
12	0.773	0.748	0.798	LinearSVC()	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	0.018	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='median')	StandardScaler()	OneHotEncoder()
13	0.773	0.747	0.798	RandomForestClassifier()	0.010	63.000	50.000	1.000	0.765	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	None	OneHotEncoder()
14	0.773	0.745	0.801	RandomForestClassifier()	0.082	10.000	50.000	1.000	0.500	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	None	OneHotEncoder()
15	0.773	0.758	0.787	RandomForestClassifier()	0.138	77.000	50.000	1.000	1.000	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	None	OneHotEncoder()
16	0.772	0.756	0.789	RandomForestClassifier()	0.070	85.000	50.000	3.000	0.500	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='median')	None	CustomOrdinalEncoder()
17	0.772	0.743	0.801	LinearSVC()	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	0.009	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	StandardScaler()	OneHotEncoder()
18	0.772	0.735	0.809	LinearSVC()	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	0.010	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	StandardScaler()	OneHotEncoder()
19	0.772	0.749	0.795	ExtraTreesClassifier()	0.010	100.000	50.000	1.000	0.883	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	None	CustomOrdinalEncoder()
20	0.772	0.745	0.798	ExtraTreesClassifier()	0.069	93.000	4.000	2.000	0.915	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	None	CustomOrdinalEncoder()
21	0.771	0.749	0.794	LinearSVC()	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	0.021	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	StandardScaler()	OneHotEncoder()
22	0.771	0.744	0.798	LogisticRegression()	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	StandardScaler()	OneHotEncoder()
23	0.771	0.737	0.805	LogisticRegression()	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	0.188	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	StandardScaler()	OneHotEncoder()
24	0.771	0.745	0.797	RandomForestClassifier()	0.144	8.000	24.000	1.000	0.994	entropy	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='median')	None	CustomOrdinalEncoder()
25	0.771	0.749	0.792	LinearSVC()	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	0.021	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	StandardScaler()	OneHotEncoder()
26	0.771	0.747	0.794	LogisticRegression()	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	0.175	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	StandardScaler()	OneHotEncoder()
27	0.770	0.752	0.787	ExtraTreesClassifier()	0.010	100.000	50.000	1.000	0.500	entropy	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	None	OneHotEncoder()
28	0.770	0.741	0.798	LinearSVC()	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	0.037	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	MinMaxScaler()	OneHotEncoder()
29	0.770	0.744	0.795	LogisticRegression()	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	0.160	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	StandardScaler()	OneHotEncoder()
30	0.769	0.744	0.795	LogisticRegression()	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	0.110	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	StandardScaler()	OneHotEncoder()
31	0.769	0.744	0.795	LinearSVC()	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	0.016	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	MinMaxScaler()	OneHotEncoder()
32	0.769	0.747	0.792	LinearSVC()	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	0.012	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	StandardScaler()	OneHotEncoder()
33	0.769	0.747	0.791	LogisticRegression()	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	0.259	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	StandardScaler()	OneHotEncoder()
34	0.769	0.742	0.796	RandomForestClassifier()	0.022	24.000	44.000	4.000	0.568	entropy	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	None	CustomOrdinalEncoder()
35	0.769	0.730	0.808	LogisticRegression()	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	0.425	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	StandardScaler()	OneHotEncoder()
36	0.769	0.744	0.794	ExtraTreesClassifier()	0.010	100.000	50.000	1.000	0.500	entropy	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	None	OneHotEncoder()
37	0.769	0.737	0.801	LogisticRegression()	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	0.017	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	MinMaxScaler()	OneHotEncoder()
38	0.769	0.758	0.779	LinearSVC()	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	0.007	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	StandardScaler()	OneHotEncoder()
39	0.769	0.735	0.803	RandomForestClassifier()	0.010	19.000	50.000	1.000	0.861	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	None	CustomOrdinalEncoder()
40	0.769	0.742	0.795	ExtraTreesClassifier()	0.010	100.000	50.000	1.000	1.000	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	None	OneHotEncoder()
41	0.769	0.747	0.791	LogisticRegression()	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	0.050	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	MinMaxScaler()	OneHotEncoder()
42	0.769	0.739	0.799	RandomForestClassifier()	0.108	75.000	50.000	7.000	0.500	entropy	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	None	OneHotEncoder()
43	0.769	0.759	0.779	RandomForestClassifier()	0.155	100.000	4.000	7.000	0.632	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='median')	None	OneHotEncoder()
44	0.769	0.747	0.790	ExtraTreesClassifier()	0.010	100.000	50.000	1.000	0.645	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	None	CustomOrdinalEncoder()
45	0.769	0.755	0.782	LogisticRegression()	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	0.204	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	StandardScaler()	OneHotEncoder()
46	0.768	0.747	0.789	LinearSVC()	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	0.006	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	StandardScaler()	OneHotEncoder()
47	0.768	0.747	0.789	LinearSVC()	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	0.674	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	StandardScaler()	OneHotEncoder()
48	0.768	0.740	0.796	LogisticRegression()	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	0.018	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	MinMaxScaler()	OneHotEncoder()
49	0.768	0.748	0.787	RandomForestClassifier()	0.194	41.000	50.000	5.000	0.500	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	None	CustomOrdinalEncoder()
50	0.768	0.735	0.801	XGBClassifier()	<NA>	2.000	<NA>	<NA>	<NA>	<NA>	<NA>	0.082	100.000	1.000	0.500	0.500	0.730	1.000	1.000	SimpleImputer(strategy='median')	None	CustomOrdinalEncoder()
51	0.768	0.745	0.790	LinearSVC()	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	0.056	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	MinMaxScaler()	OneHotEncoder()
52	0.768	0.737	0.799	ExtraTreesClassifier()	0.010	100.000	50.000	1.000	0.500	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	None	OneHotEncoder()
53	0.767	0.740	0.795	LogisticRegression()	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	0.777	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	StandardScaler()	OneHotEncoder()
54	0.767	0.744	0.791	LinearSVC()	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	0.021	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	MinMaxScaler()	OneHotEncoder()
55	0.767	0.743	0.792	LinearSVC()	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	0.136	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	MinMaxScaler()	OneHotEncoder()
56	0.767	0.741	0.793	RandomForestClassifier()	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	None	OneHotEncoder()
57	0.767	0.742	0.792	LinearSVC()	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	0.016	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	StandardScaler()	OneHotEncoder()
58	0.767	0.734	0.799	ExtraTreesClassifier()	0.010	100.000	50.000	1.000	0.676	entropy	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	None	CustomOrdinalEncoder()
59	0.767	0.735	0.798	ExtraTreesClassifier()	0.010	100.000	50.000	1.000	0.836	entropy	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	None	CustomOrdinalEncoder()
60	0.766	0.743	0.790	LinearSVC()	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	0.042	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	StandardScaler()	OneHotEncoder()
61	0.766	0.740	0.793	ExtraTreesClassifier()	0.010	100.000	50.000	1.000	1.000	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	None	OneHotEncoder()
62	0.766	0.737	0.796	LinearSVC()	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	0.011	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	StandardScaler()	OneHotEncoder()
63	0.766	0.734	0.798	XGBClassifier()	<NA>	6.000	<NA>	<NA>	<NA>	<NA>	<NA>	0.000	1,082.000	1.000	0.500	0.522	0.597	0.221	1.313	SimpleImputer(strategy='median')	None	OneHotEncoder()
64	0.766	0.746	0.786	LinearSVC()	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	0.003	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	StandardScaler()	OneHotEncoder()
65	0.766	0.738	0.793	ExtraTreesClassifier()	0.010	100.000	50.000	1.000	1.000	entropy	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	None	OneHotEncoder()
66	0.766	0.742	0.789	LinearSVC()	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	0.293	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	MinMaxScaler()	OneHotEncoder()
67	0.766	0.742	0.789	XGBClassifier()	<NA>	11.000	<NA>	<NA>	<NA>	<NA>	<NA>	0.054	100.000	1.000	0.500	0.500	0.796	1.000	1.000	SimpleImputer(strategy='median')	None	CustomOrdinalEncoder()
68	0.765	0.734	0.797	LogisticRegression()	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	3.026	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	StandardScaler()	OneHotEncoder()
69	0.765	0.737	0.794	XGBClassifier()	<NA>	3.000	<NA>	<NA>	<NA>	<NA>	<NA>	0.000	167.000	1.000	0.500	0.500	0.746	0.767	1.194	SimpleImputer(strategy='most_frequent')	None	CustomOrdinalEncoder()
70	0.765	0.745	0.786	XGBClassifier()	<NA>	13.000	<NA>	<NA>	<NA>	<NA>	<NA>	0.000	558.000	1.000	0.500	0.597	0.564	0.187	1.218	SimpleImputer(strategy='median')	None	CustomOrdinalEncoder()
71	0.765	0.736	0.794	ExtraTreesClassifier()	0.010	1.000	50.000	1.000	1.000	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	None	OneHotEncoder()
72	0.765	0.732	0.798	ExtraTreesClassifier()	0.034	15.000	30.000	1.000	0.604	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='median')	None	CustomOrdinalEncoder()
73	0.765	0.746	0.783	LinearSVC()	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	0.008	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	MinMaxScaler()	OneHotEncoder()
74	0.764	0.741	0.788	LogisticRegression()	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	0.245	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	StandardScaler()	OneHotEncoder()
75	0.764	0.741	0.787	LinearSVC()	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	0.153	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	StandardScaler()	OneHotEncoder()
76	0.764	0.740	0.789	LinearSVC()	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	6.764	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	MinMaxScaler()	OneHotEncoder()
77	0.764	0.732	0.795	RandomForestClassifier()	0.072	80.000	50.000	16.000	0.644	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	None	OneHotEncoder()
78	0.763	0.740	0.787	LogisticRegression()	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	0.054	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	MinMaxScaler()	OneHotEncoder()
79	0.763	0.746	0.780	ExtraTreesClassifier()	0.931	99.000	36.000	4.000	0.778	entropy	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='median')	None	OneHotEncoder()
80	0.763	0.739	0.788	LogisticRegression()	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	1.076	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	MinMaxScaler()	OneHotEncoder()
81	0.763	0.744	0.782	RandomForestClassifier()	0.010	22.000	2.000	1.000	0.765	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	None	OneHotEncoder()
82	0.763	0.739	0.787	LogisticRegression()	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	0.249	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	StandardScaler()	OneHotEncoder()
83	0.763	0.736	0.790	RandomForestClassifier()	0.010	4.000	45.000	15.000	0.602	entropy	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='median')	None	OneHotEncoder()
84	0.762	0.728	0.796	LinearSVC()	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	0.158	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	StandardScaler()	OneHotEncoder()
85	0.762	0.732	0.792	LinearSVC()	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	0.001	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	StandardScaler()	OneHotEncoder()
86	0.762	0.744	0.781	LogisticRegression()	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	0.442	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	StandardScaler()	OneHotEncoder()
87	0.762	0.742	0.782	ExtraTreesClassifier()	0.010	100.000	2.000	1.000	0.500	entropy	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	None	CustomOrdinalEncoder()
88	0.762	0.739	0.784	ExtraTreesClassifier()	0.021	1.000	36.000	1.000	0.830	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	None	OneHotEncoder()
89	0.761	0.740	0.782	RandomForestClassifier()	0.014	72.000	4.000	24.000	0.569	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='median')	None	OneHotEncoder()
90	0.761	0.734	0.789	LogisticRegression()	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	38.539	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	StandardScaler()	OneHotEncoder()
91	0.761	0.742	0.781	RandomForestClassifier()	0.014	4.000	12.000	32.000	0.855	entropy	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='median')	None	OneHotEncoder()
92	0.761	0.729	0.793	LogisticRegression()	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	0.167	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	StandardScaler()	OneHotEncoder()
93	0.761	0.744	0.778	LogisticRegression()	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	0.000	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	MinMaxScaler()	OneHotEncoder()
94	0.761	0.738	0.784	ExtraTreesClassifier()	0.010	100.000	50.000	1.000	1.000	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	None	CustomOrdinalEncoder()
95	0.760	0.733	0.788	LinearSVC()	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	0.064	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	StandardScaler()	OneHotEncoder()
96	0.760	0.734	0.786	LinearSVC()	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	3.267	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	StandardScaler()	OneHotEncoder()
97	0.760	0.738	0.782	ExtraTreesClassifier()	0.914	6.000	44.000	2.000	0.629	entropy	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	None	OneHotEncoder()
98	0.760	0.729	0.790	XGBClassifier()	<NA>	3.000	<NA>	<NA>	<NA>	<NA>	<NA>	0.000	100.000	1.000	0.519	0.500	0.535	0.000	1.000	SimpleImputer(strategy='most_frequent')	None	CustomOrdinalEncoder()
99	0.760	0.728	0.791	RandomForestClassifier()	0.010	77.000	50.000	16.000	0.845	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	None	CustomOrdinalEncoder()
100	0.760	0.732	0.787	LogisticRegression()	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	0.512	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	StandardScaler()	OneHotEncoder()
101	0.759	0.735	0.783	LogisticRegression()	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	0.270	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	MinMaxScaler()	OneHotEncoder()
102	0.759	0.724	0.794	XGBClassifier()	<NA>	43.000	<NA>	<NA>	<NA>	<NA>	<NA>	0.000	593.000	1.000	0.550	0.500	0.759	0.006	1.000	SimpleImputer()	None	CustomOrdinalEncoder()
103	0.759	0.739	0.780	RandomForestClassifier()	0.548	21.000	20.000	1.000	0.919	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	None	CustomOrdinalEncoder()
104	0.759	0.743	0.775	ExtraTreesClassifier()	0.913	30.000	44.000	2.000	0.963	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	None	OneHotEncoder()
105	0.759	0.735	0.782	LogisticRegression()	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	0.000	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='median')	MinMaxScaler()	OneHotEncoder()
106	0.759	0.737	0.780	ExtraTreesClassifier()	0.010	100.000	2.000	1.000	0.500	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	None	OneHotEncoder()
107	0.758	0.731	0.786	ExtraTreesClassifier()	0.010	100.000	50.000	1.000	1.000	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	None	CustomOrdinalEncoder()
108	0.758	0.736	0.781	ExtraTreesClassifier()	0.416	73.000	48.000	1.000	0.852	entropy	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	None	CustomOrdinalEncoder()
109	0.758	0.726	0.791	LogisticRegression()	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	0.029	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	MinMaxScaler()	OneHotEncoder()
110	0.758	0.729	0.787	LogisticRegression()	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	0.001	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	MinMaxScaler()	OneHotEncoder()
111	0.758	0.725	0.790	ExtraTreesClassifier()	0.950	100.000	50.000	1.000	0.585	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	None	CustomOrdinalEncoder()
112	0.758	0.729	0.786	LogisticRegression()	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	0.000	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='median')	MinMaxScaler()	OneHotEncoder()
113	0.758	0.734	0.781	ExtraTreesClassifier()	0.652	98.000	45.000	1.000	0.642	entropy	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='median')	None	CustomOrdinalEncoder()
114	0.758	0.726	0.789	ExtraTreesClassifier()	0.011	14.000	46.000	15.000	0.660	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='median')	None	OneHotEncoder()
115	0.757	0.725	0.790	RandomForestClassifier()	0.682	16.000	47.000	2.000	0.973	entropy	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	None	CustomOrdinalEncoder()
116	0.757	0.726	0.788	RandomForestClassifier()	0.356	71.000	3.000	1.000	0.945	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	None	OneHotEncoder()
117	0.757	0.730	0.785	LinearSVC()	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	0.003	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	MinMaxScaler()	OneHotEncoder()
118	0.757	0.733	0.781	LinearSVC()	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	1.670	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	StandardScaler()	OneHotEncoder()
119	0.757	0.730	0.784	XGBClassifier()	<NA>	1.000	<NA>	<NA>	<NA>	<NA>	<NA>	0.195	100.000	1.000	1.000	1.000	0.509	0.000	1.000	SimpleImputer(strategy='most_frequent')	None	CustomOrdinalEncoder()
120	0.757	0.721	0.793	RandomForestClassifier()	0.075	1.000	50.000	6.000	1.000	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	None	OneHotEncoder()
121	0.757	0.728	0.786	ExtraTreesClassifier()	0.700	38.000	18.000	1.000	0.514	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='median')	None	OneHotEncoder()
122	0.756	0.736	0.776	XGBClassifier()	<NA>	50.000	<NA>	<NA>	<NA>	<NA>	<NA>	0.026	238.000	3.000	0.500	0.566	1.000	1.000	1.188	SimpleImputer()	None	OneHotEncoder()
123	0.756	0.721	0.792	RandomForestClassifier()	0.185	74.000	15.000	21.000	0.547	entropy	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	None	CustomOrdinalEncoder()
124	0.756	0.724	0.789	ExtraTreesClassifier()	0.473	25.000	48.000	6.000	0.631	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='median')	None	OneHotEncoder()
125	0.756	0.737	0.776	RandomForestClassifier()	0.474	100.000	50.000	1.000	0.500	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	None	OneHotEncoder()
126	0.756	0.734	0.778	LogisticRegression()	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	100.000	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	MinMaxScaler()	OneHotEncoder()
127	0.756	0.732	0.781	LogisticRegression()	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	4.069	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	StandardScaler()	OneHotEncoder()
128	0.756	0.729	0.783	RandomForestClassifier()	0.916	5.000	49.000	3.000	0.578	entropy	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='median')	None	OneHotEncoder()
129	0.756	0.741	0.771	LogisticRegression()	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	100.000	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	StandardScaler()	OneHotEncoder()
130	0.756	0.738	0.773	LinearSVC()	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	0.001	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	StandardScaler()	OneHotEncoder()
131	0.756	0.709	0.802	LogisticRegression()	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	0.000	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	MinMaxScaler()	OneHotEncoder()
132	0.755	0.723	0.788	ExtraTreesClassifier()	0.895	9.000	48.000	2.000	0.502	entropy	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='median')	None	CustomOrdinalEncoder()
133	0.755	0.727	0.783	XGBClassifier()	<NA>	1.000	<NA>	<NA>	<NA>	<NA>	<NA>	0.315	100.000	1.000	1.000	1.000	0.694	1.000	4.000	SimpleImputer(strategy='median')	None	CustomOrdinalEncoder()
134	0.755	0.730	0.780	LinearSVC()	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	StandardScaler()	OneHotEncoder()
135	0.755	0.719	0.791	XGBClassifier()	<NA>	4.000	<NA>	<NA>	<NA>	<NA>	<NA>	0.000	2,000.000	1.000	0.500	0.552	1.000	0.001	1.163	SimpleImputer()	None	OneHotEncoder()
136	0.755	0.734	0.776	RandomForestClassifier()	0.366	82.000	41.000	6.000	0.550	entropy	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	None	CustomOrdinalEncoder()
137	0.754	0.738	0.770	XGBClassifier()	<NA>	26.000	<NA>	<NA>	<NA>	<NA>	<NA>	0.066	109.000	1.000	0.500	1.000	0.747	0.000	1.000	SimpleImputer(strategy='median')	None	OneHotEncoder()
138	0.754	0.737	0.771	ExtraTreesClassifier()	0.425	21.000	50.000	2.000	0.622	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	None	OneHotEncoder()
139	0.754	0.723	0.785	XGBClassifier()	<NA>	3.000	<NA>	<NA>	<NA>	<NA>	<NA>	0.062	173.000	3.000	0.545	0.801	0.806	0.000	1.009	SimpleImputer(strategy='median')	None	CustomOrdinalEncoder()
140	0.754	0.724	0.784	LogisticRegression()	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	0.001	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	MinMaxScaler()	OneHotEncoder()
141	0.754	0.725	0.783	RandomForestClassifier()	0.652	100.000	3.000	3.000	0.515	entropy	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	None	CustomOrdinalEncoder()
142	0.754	0.732	0.775	ExtraTreesClassifier()	0.950	44.000	45.000	12.000	0.895	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	None	OneHotEncoder()
143	0.754	0.719	0.788	RandomForestClassifier()	0.010	1.000	47.000	48.000	1.000	entropy	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	None	OneHotEncoder()
144	0.754	0.722	0.786	ExtraTreesClassifier()	0.281	100.000	2.000	1.000	1.000	entropy	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	None	OneHotEncoder()
145	0.754	0.737	0.770	ExtraTreesClassifier()	0.948	18.000	3.000	6.000	0.945	entropy	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	None	OneHotEncoder()
146	0.754	0.725	0.782	ExtraTreesClassifier()	0.875	96.000	41.000	1.000	0.963	entropy	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='median')	None	OneHotEncoder()
147	0.753	0.729	0.778	XGBClassifier()	<NA>	50.000	<NA>	<NA>	<NA>	<NA>	<NA>	0.000	100.000	2.000	0.500	0.629	1.000	0.697	1.535	SimpleImputer(strategy='median')	None	OneHotEncoder()
148	0.753	0.725	0.782	RandomForestClassifier()	0.010	100.000	2.000	1.000	1.000	entropy	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	None	CustomOrdinalEncoder()
149	0.753	0.728	0.779	ExtraTreesClassifier()	0.362	85.000	5.000	10.000	0.899	entropy	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='median')	None	CustomOrdinalEncoder()
150	0.753	0.738	0.769	ExtraTreesClassifier()	0.875	69.000	4.000	1.000	0.690	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='median')	None	CustomOrdinalEncoder()
151	0.753	0.727	0.778	LinearSVC()	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	3.787	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	MinMaxScaler()	OneHotEncoder()
152	0.752	0.724	0.780	LogisticRegression()	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	0.000	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	MinMaxScaler()	OneHotEncoder()
153	0.752	0.726	0.779	XGBClassifier()	<NA>	1.000	<NA>	<NA>	<NA>	<NA>	<NA>	0.248	100.000	1.000	1.000	0.500	0.967	1.000	1.000	SimpleImputer(strategy='median')	None	OneHotEncoder()
154	0.752	0.730	0.775	RandomForestClassifier()	0.046	23.000	49.000	33.000	0.882	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='median')	None	CustomOrdinalEncoder()
155	0.752	0.721	0.783	LinearSVC()	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	0.820	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	MinMaxScaler()	OneHotEncoder()
156	0.752	0.715	0.788	ExtraTreesClassifier()	0.013	82.000	48.000	17.000	0.875	entropy	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	None	CustomOrdinalEncoder()
157	0.751	0.721	0.782	LinearSVC()	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	10.805	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	StandardScaler()	OneHotEncoder()
158	0.751	0.720	0.782	LogisticRegression()	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	0.003	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	StandardScaler()	OneHotEncoder()
159	0.751	0.721	0.781	XGBClassifier()	<NA>	2.000	<NA>	<NA>	<NA>	<NA>	<NA>	0.000	591.000	1.000	0.500	0.500	0.805	1.000	1.000	SimpleImputer(strategy='median')	None	CustomOrdinalEncoder()
160	0.751	0.721	0.780	LogisticRegression()	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	100.000	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	MinMaxScaler()	OneHotEncoder()
161	0.751	0.730	0.772	LogisticRegression()	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	0.000	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	MinMaxScaler()	OneHotEncoder()
162	0.750	0.727	0.773	ExtraTreesClassifier()	0.300	96.000	21.000	20.000	0.746	entropy	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	None	OneHotEncoder()
163	0.750	0.727	0.773	ExtraTreesClassifier()	0.051	1.000	9.000	2.000	0.682	entropy	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	None	OneHotEncoder()
164	0.750	0.729	0.770	ExtraTreesClassifier()	0.030	84.000	24.000	36.000	0.981	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	None	OneHotEncoder()
165	0.749	0.719	0.780	LogisticRegression()	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	2.387	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	MinMaxScaler()	OneHotEncoder()
166	0.749	0.715	0.783	ExtraTreesClassifier()	0.016	59.000	49.000	49.000	0.833	entropy	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	None	OneHotEncoder()
167	0.748	0.727	0.770	ExtraTreesClassifier()	0.014	92.000	7.000	22.000	0.882	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	None	CustomOrdinalEncoder()
168	0.748	0.714	0.781	RandomForestClassifier()	0.490	98.000	35.000	15.000	0.935	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	None	OneHotEncoder()
169	0.747	0.726	0.769	XGBClassifier()	<NA>	6.000	<NA>	<NA>	<NA>	<NA>	<NA>	0.000	1,750.000	4.000	0.500	1.000	0.744	0.001	1.000	SimpleImputer(strategy='most_frequent')	None	OneHotEncoder()
170	0.747	0.714	0.780	ExtraTreesClassifier()	0.010	1.000	50.000	1.000	0.739	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	None	CustomOrdinalEncoder()
171	0.747	0.729	0.764	ExtraTreesClassifier()	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	None	OneHotEncoder()
172	0.747	0.729	0.764	XGBClassifier()	<NA>	1.000	<NA>	<NA>	<NA>	<NA>	<NA>	0.000	147.000	1.000	0.500	0.500	0.500	0.000	2.230	SimpleImputer(strategy='most_frequent')	None	CustomOrdinalEncoder()
173	0.746	0.720	0.772	XGBClassifier()	<NA>	1.000	<NA>	<NA>	<NA>	<NA>	<NA>	0.500	2,000.000	1.000	1.000	1.000	0.667	1.000	4.000	SimpleImputer(strategy='most_frequent')	None	CustomOrdinalEncoder()
174	0.746	0.712	0.780	RandomForestClassifier()	0.653	2.000	44.000	1.000	0.502	entropy	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	None	OneHotEncoder()
175	0.746	0.715	0.777	XGBClassifier()	<NA>	17.000	<NA>	<NA>	<NA>	<NA>	<NA>	0.000	100.000	5.000	0.500	0.938	0.941	0.000	1.000	SimpleImputer(strategy='median')	None	OneHotEncoder()
176	0.746	0.725	0.766	XGBClassifier()	<NA>	2.000	<NA>	<NA>	<NA>	<NA>	<NA>	0.077	617.000	1.000	0.652	0.776	0.500	0.269	1.000	SimpleImputer()	None	CustomOrdinalEncoder()
177	0.744	0.712	0.776	LogisticRegression()	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	0.002	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	StandardScaler()	OneHotEncoder()
178	0.744	0.715	0.773	XGBClassifier()	<NA>	37.000	<NA>	<NA>	<NA>	<NA>	<NA>	0.000	1,306.000	1.000	0.691	1.000	0.819	0.080	1.000	SimpleImputer()	None	CustomOrdinalEncoder()
179	0.744	0.719	0.768	RandomForestClassifier()	0.523	47.000	20.000	27.000	0.602	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	None	CustomOrdinalEncoder()
180	0.744	0.714	0.773	XGBClassifier()	<NA>	1.000	<NA>	<NA>	<NA>	<NA>	<NA>	0.038	2,000.000	10.000	0.500	0.500	0.559	1.000	1.000	SimpleImputer(strategy='most_frequent')	None	CustomOrdinalEncoder()
181	0.743	0.720	0.766	LogisticRegression()	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	100.000	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	StandardScaler()	OneHotEncoder()
182	0.742	0.724	0.761	XGBClassifier()	<NA>	1.000	<NA>	<NA>	<NA>	<NA>	<NA>	0.000	2,000.000	2.000	0.500	0.881	0.500	0.000	1.000	SimpleImputer(strategy='most_frequent')	None	CustomOrdinalEncoder()
183	0.742	0.713	0.772	RandomForestClassifier()	0.941	92.000	4.000	18.000	0.569	entropy	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	None	CustomOrdinalEncoder()
184	0.742	0.724	0.760	RandomForestClassifier()	0.875	2.000	13.000	1.000	0.535	entropy	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	None	CustomOrdinalEncoder()
185	0.742	0.705	0.778	XGBClassifier()	<NA>	2.000	<NA>	<NA>	<NA>	<NA>	<NA>	0.000	136.000	2.000	0.500	0.796	0.657	0.000	1.000	SimpleImputer(strategy='most_frequent')	None	OneHotEncoder()
186	0.741	0.717	0.765	RandomForestClassifier()	0.010	98.000	38.000	50.000	0.532	entropy	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	None	CustomOrdinalEncoder()
187	0.741	0.703	0.779	ExtraTreesClassifier()	0.134	82.000	2.000	50.000	0.554	entropy	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='median')	None	OneHotEncoder()
188	0.741	0.722	0.759	LinearSVC()	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	1.557	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	StandardScaler()	CustomOrdinalEncoder()
189	0.740	0.718	0.762	RandomForestClassifier()	0.711	59.000	41.000	21.000	0.519	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	None	OneHotEncoder()
190	0.739	0.717	0.761	RandomForestClassifier()	0.337	2.000	23.000	21.000	0.559	entropy	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='median')	None	OneHotEncoder()
191	0.737	0.714	0.760	LinearSVC()	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	0.001	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	StandardScaler()	CustomOrdinalEncoder()
192	0.737	0.716	0.758	ExtraTreesClassifier()	0.559	72.000	35.000	32.000	0.630	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='median')	None	CustomOrdinalEncoder()
193	0.737	0.706	0.767	ExtraTreesClassifier()	0.492	49.000	32.000	36.000	0.682	entropy	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	None	OneHotEncoder()
194	0.737	0.720	0.753	XGBClassifier()	<NA>	18.000	<NA>	<NA>	<NA>	<NA>	<NA>	0.500	249.000	1.000	1.000	1.000	0.672	0.391	4.000	SimpleImputer(strategy='most_frequent')	None	CustomOrdinalEncoder()
195	0.736	0.716	0.756	XGBClassifier()	<NA>	3.000	<NA>	<NA>	<NA>	<NA>	<NA>	0.000	1,450.000	4.000	0.988	0.754	0.945	0.000	1.000	SimpleImputer(strategy='median')	None	CustomOrdinalEncoder()
196	0.736	0.709	0.763	RandomForestClassifier()	0.629	21.000	11.000	42.000	0.565	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='median')	None	CustomOrdinalEncoder()
197	0.735	0.719	0.752	RandomForestClassifier()	0.932	14.000	41.000	33.000	0.507	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	None	CustomOrdinalEncoder()
198	0.735	0.703	0.768	ExtraTreesClassifier()	0.672	81.000	34.000	34.000	0.971	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='median')	None	OneHotEncoder()
199	0.735	0.713	0.757	ExtraTreesClassifier()	0.011	10.000	18.000	49.000	0.766	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	None	CustomOrdinalEncoder()
200	0.735	0.685	0.784	ExtraTreesClassifier()	0.857	30.000	17.000	28.000	0.563	entropy	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='median')	None	OneHotEncoder()
201	0.734	0.703	0.764	LogisticRegression()	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	0.000	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	StandardScaler()	OneHotEncoder()
202	0.734	0.698	0.770	RandomForestClassifier()	0.238	1.000	2.000	50.000	1.000	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='median')	None	OneHotEncoder()
203	0.733	0.710	0.756	LogisticRegression()	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	0.560	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	StandardScaler()	CustomOrdinalEncoder()
204	0.733	0.718	0.747	RandomForestClassifier()	0.565	90.000	35.000	44.000	0.613	entropy	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='median')	None	OneHotEncoder()
205	0.732	0.705	0.760	LogisticRegression()	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	0.003	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	StandardScaler()	CustomOrdinalEncoder()
206	0.732	0.698	0.766	XGBClassifier()	<NA>	1.000	<NA>	<NA>	<NA>	<NA>	<NA>	0.000	100.000	1.000	0.500	1.000	0.552	0.329	1.705	SimpleImputer(strategy='most_frequent')	None	CustomOrdinalEncoder()
207	0.732	0.712	0.752	RandomForestClassifier()	0.950	100.000	2.000	1.000	1.000	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	None	CustomOrdinalEncoder()
208	0.732	0.701	0.763	LogisticRegression()	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	30.308	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='median')	MinMaxScaler()	CustomOrdinalEncoder()
209	0.731	0.707	0.756	ExtraTreesClassifier()	0.938	83.000	4.000	49.000	0.712	entropy	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='median')	None	CustomOrdinalEncoder()
210	0.730	0.715	0.746	LinearSVC()	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	0.016	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='median')	StandardScaler()	CustomOrdinalEncoder()
211	0.730	0.708	0.752	ExtraTreesClassifier()	0.781	50.000	35.000	47.000	0.846	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='median')	None	OneHotEncoder()
212	0.730	0.710	0.749	LogisticRegression()	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	0.000	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	StandardScaler()	OneHotEncoder()
213	0.729	0.710	0.748	XGBClassifier()	<NA>	1.000	<NA>	<NA>	<NA>	<NA>	<NA>	0.000	2,000.000	2.000	0.500	1.000	0.500	0.000	3.531	SimpleImputer(strategy='median')	None	OneHotEncoder()
214	0.729	0.701	0.757	LogisticRegression()	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	96.799	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	StandardScaler()	CustomOrdinalEncoder()
215	0.729	0.712	0.746	LogisticRegression()	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	1.452	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='median')	MinMaxScaler()	CustomOrdinalEncoder()
216	0.728	0.709	0.747	XGBClassifier()	<NA>	2.000	<NA>	<NA>	<NA>	<NA>	<NA>	0.186	261.000	12.000	0.820	0.973	0.738	0.091	1.706	SimpleImputer(strategy='median')	None	CustomOrdinalEncoder()
217	0.727	0.709	0.746	LinearSVC()	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	0.074	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	MinMaxScaler()	CustomOrdinalEncoder()
218	0.727	0.691	0.763	XGBClassifier()	<NA>	1.000	<NA>	<NA>	<NA>	<NA>	<NA>	0.449	242.000	3.000	0.787	0.918	0.691	0.030	2.709	SimpleImputer()	None	CustomOrdinalEncoder()
219	0.726	0.699	0.753	LinearSVC()	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	0.415	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	MinMaxScaler()	CustomOrdinalEncoder()
220	0.726	0.684	0.768	XGBClassifier()	<NA>	1.000	<NA>	<NA>	<NA>	<NA>	<NA>	0.000	119.000	1.000	0.864	0.552	0.641	0.000	1.385	SimpleImputer(strategy='most_frequent')	None	CustomOrdinalEncoder()
221	0.726	0.700	0.751	XGBClassifier()	<NA>	9.000	<NA>	<NA>	<NA>	<NA>	<NA>	0.135	171.000	3.000	0.500	1.000	0.898	0.834	4.000	SimpleImputer(strategy='median')	None	OneHotEncoder()
222	0.725	0.706	0.743	LogisticRegression()	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	0.000	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='median')	StandardScaler()	CustomOrdinalEncoder()
223	0.724	0.706	0.743	XGBClassifier()	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	None	OneHotEncoder()
224	0.724	0.697	0.751	XGBClassifier()	<NA>	2.000	<NA>	<NA>	<NA>	<NA>	<NA>	0.500	126.000	1.000	0.931	1.000	0.714	0.476	1.341	SimpleImputer()	None	CustomOrdinalEncoder()
225	0.723	0.688	0.759	LinearSVC()	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	0.007	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='median')	MinMaxScaler()	CustomOrdinalEncoder()
226	0.723	0.705	0.740	RandomForestClassifier()	0.950	100.000	37.000	50.000	1.000	entropy	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	None	OneHotEncoder()
227	0.721	0.684	0.758	XGBClassifier()	<NA>	3.000	<NA>	<NA>	<NA>	<NA>	<NA>	0.068	1,485.000	2.000	0.500	0.500	0.885	0.141	4.000	SimpleImputer()	None	OneHotEncoder()
228	0.721	0.704	0.738	XGBClassifier()	<NA>	50.000	<NA>	<NA>	<NA>	<NA>	<NA>	0.085	2,000.000	1.000	0.500	0.500	1.000	1.000	1.291	SimpleImputer()	None	CustomOrdinalEncoder()
229	0.719	0.696	0.743	XGBClassifier()	<NA>	19.000	<NA>	<NA>	<NA>	<NA>	<NA>	0.089	429.000	10.000	0.736	0.878	0.550	0.002	1.131	SimpleImputer(strategy='median')	None	OneHotEncoder()
230	0.719	0.693	0.745	LinearSVC()	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	5.269	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	MinMaxScaler()	CustomOrdinalEncoder()
231	0.718	0.687	0.750	XGBClassifier()	<NA>	36.000	<NA>	<NA>	<NA>	<NA>	<NA>	0.073	1,465.000	2.000	0.653	0.785	0.588	0.325	2.062	SimpleImputer(strategy='median')	None	CustomOrdinalEncoder()
232	0.718	0.701	0.734	XGBClassifier()	<NA>	21.000	<NA>	<NA>	<NA>	<NA>	<NA>	0.235	135.000	2.000	0.689	0.824	0.979	0.032	1.872	SimpleImputer(strategy='median')	None	CustomOrdinalEncoder()
233	0.717	0.689	0.745	XGBClassifier()	<NA>	8.000	<NA>	<NA>	<NA>	<NA>	<NA>	0.500	472.000	1.000	0.500	0.500	0.781	0.032	1.371	SimpleImputer(strategy='median')	None	CustomOrdinalEncoder()
234	0.717	0.684	0.751	LinearSVC()	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	0.000	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='median')	StandardScaler()	OneHotEncoder()
235	0.712	0.698	0.725	XGBClassifier()	<NA>	32.000	<NA>	<NA>	<NA>	<NA>	<NA>	0.483	281.000	2.000	0.843	0.699	0.784	0.000	1.000	SimpleImputer(strategy='median')	None	OneHotEncoder()
236	0.711	0.693	0.729	XGBClassifier()	<NA>	7.000	<NA>	<NA>	<NA>	<NA>	<NA>	0.278	1,692.000	4.000	0.936	0.805	0.688	0.000	1.674	SimpleImputer(strategy='median')	None	CustomOrdinalEncoder()
237	0.711	0.684	0.738	LinearSVC()	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	0.000	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	MinMaxScaler()	OneHotEncoder()
238	0.708	0.672	0.745	LogisticRegression()	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	0.004	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	MinMaxScaler()	CustomOrdinalEncoder()
239	0.708	0.679	0.737	LinearSVC()	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	0.000	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	StandardScaler()	OneHotEncoder()
240	0.707	0.685	0.730	LinearSVC()	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	0.000	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	StandardScaler()	OneHotEncoder()
241	0.705	0.681	0.729	LogisticRegression()	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	0.000	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='median')	MinMaxScaler()	CustomOrdinalEncoder()
242	0.703	0.683	0.724	LinearSVC()	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	0.000	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	MinMaxScaler()	CustomOrdinalEncoder()
243	0.701	0.674	0.729	XGBClassifier()	<NA>	10.000	<NA>	<NA>	<NA>	<NA>	<NA>	0.395	131.000	3.000	0.500	1.000	0.873	1.000	1.000	SimpleImputer(strategy='median')	None	CustomOrdinalEncoder()
244	0.700	0.666	0.735	XGBClassifier()	<NA>	17.000	<NA>	<NA>	<NA>	<NA>	<NA>	0.221	400.000	2.000	0.500	1.000	0.822	0.045	1.000	SimpleImputer()	None	CustomOrdinalEncoder()
245	0.699	0.674	0.725	LinearSVC()	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	100.000	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	StandardScaler()	OneHotEncoder()
246	0.699	0.666	0.732	XGBClassifier()	<NA>	6.000	<NA>	<NA>	<NA>	<NA>	<NA>	0.153	1,510.000	10.000	0.873	0.543	0.701	0.853	1.133	SimpleImputer(strategy='median')	None	OneHotEncoder()
247	0.699	0.659	0.738	LinearSVC()	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	100.000	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	MinMaxScaler()	OneHotEncoder()
248	0.698	0.665	0.731	XGBClassifier()	<NA>	33.000	<NA>	<NA>	<NA>	<NA>	<NA>	0.372	923.000	20.000	0.968	0.850	0.978	0.022	2.465	SimpleImputer(strategy='median')	None	OneHotEncoder()
249	0.698	0.670	0.725	XGBClassifier()	<NA>	3.000	<NA>	<NA>	<NA>	<NA>	<NA>	0.000	385.000	50.000	0.985	1.000	0.611	0.082	4.000	SimpleImputer()	None	OneHotEncoder()
250	0.695	0.671	0.719	XGBClassifier()	<NA>	5.000	<NA>	<NA>	<NA>	<NA>	<NA>	0.402	2,000.000	28.000	0.500	0.858	1.000	1.000	1.000	SimpleImputer()	None	CustomOrdinalEncoder()
251	0.685	0.651	0.720	LinearSVC()	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	0.000	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	StandardScaler()	CustomOrdinalEncoder()
252	0.684	0.651	0.718	XGBClassifier()	<NA>	3.000	<NA>	<NA>	<NA>	<NA>	<NA>	0.457	226.000	7.000	0.648	0.646	0.774	0.000	2.574	SimpleImputer()	None	CustomOrdinalEncoder()
253	0.682	0.649	0.714	XGBClassifier()	<NA>	2.000	<NA>	<NA>	<NA>	<NA>	<NA>	0.261	1,066.000	13.000	0.692	0.780	0.801	0.002	2.561	SimpleImputer(strategy='most_frequent')	None	CustomOrdinalEncoder()
254	0.666	0.614	0.717	LinearSVC()	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	100.000	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	StandardScaler()	CustomOrdinalEncoder()
255	0.664	0.635	0.694	LinearSVC()	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	0.000	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='median')	MinMaxScaler()	CustomOrdinalEncoder()

results.to_formatted_dataframe(query='model == "XGBClassifier()"', include_rank=True)

rank	roc_auc Mean	roc_auc 95CI.LO	roc_auc 95CI.HI	max_depth	learning_rate	n_estimators	min_child_weight	subsample	colsample_bytree	colsample_bylevel	reg_alpha	reg_lambda	imputer	encoder
1	0.768	0.735	0.801	2.000	0.082	100.000	1.000	0.500	0.500	0.730	1.000	1.000	SimpleImputer(strategy='median')	CustomOrdinalEncoder()
2	0.766	0.734	0.798	6.000	0.000	1,082.000	1.000	0.500	0.522	0.597	0.221	1.313	SimpleImputer(strategy='median')	OneHotEncoder()
3	0.766	0.742	0.789	11.000	0.054	100.000	1.000	0.500	0.500	0.796	1.000	1.000	SimpleImputer(strategy='median')	CustomOrdinalEncoder()
4	0.765	0.737	0.794	3.000	0.000	167.000	1.000	0.500	0.500	0.746	0.767	1.194	SimpleImputer(strategy='most_frequent')	CustomOrdinalEncoder()
5	0.765	0.745	0.786	13.000	0.000	558.000	1.000	0.500	0.597	0.564	0.187	1.218	SimpleImputer(strategy='median')	CustomOrdinalEncoder()
6	0.760	0.729	0.790	3.000	0.000	100.000	1.000	0.519	0.500	0.535	0.000	1.000	SimpleImputer(strategy='most_frequent')	CustomOrdinalEncoder()
7	0.759	0.724	0.794	43.000	0.000	593.000	1.000	0.550	0.500	0.759	0.006	1.000	SimpleImputer()	CustomOrdinalEncoder()
8	0.757	0.730	0.784	1.000	0.195	100.000	1.000	1.000	1.000	0.509	0.000	1.000	SimpleImputer(strategy='most_frequent')	CustomOrdinalEncoder()
9	0.756	0.736	0.776	50.000	0.026	238.000	3.000	0.500	0.566	1.000	1.000	1.188	SimpleImputer()	OneHotEncoder()
10	0.755	0.727	0.783	1.000	0.315	100.000	1.000	1.000	1.000	0.694	1.000	4.000	SimpleImputer(strategy='median')	CustomOrdinalEncoder()
11	0.755	0.719	0.791	4.000	0.000	2,000.000	1.000	0.500	0.552	1.000	0.001	1.163	SimpleImputer()	OneHotEncoder()
12	0.754	0.738	0.770	26.000	0.066	109.000	1.000	0.500	1.000	0.747	0.000	1.000	SimpleImputer(strategy='median')	OneHotEncoder()
13	0.754	0.723	0.785	3.000	0.062	173.000	3.000	0.545	0.801	0.806	0.000	1.009	SimpleImputer(strategy='median')	CustomOrdinalEncoder()
14	0.753	0.729	0.778	50.000	0.000	100.000	2.000	0.500	0.629	1.000	0.697	1.535	SimpleImputer(strategy='median')	OneHotEncoder()
15	0.752	0.726	0.779	1.000	0.248	100.000	1.000	1.000	0.500	0.967	1.000	1.000	SimpleImputer(strategy='median')	OneHotEncoder()
16	0.751	0.721	0.781	2.000	0.000	591.000	1.000	0.500	0.500	0.805	1.000	1.000	SimpleImputer(strategy='median')	CustomOrdinalEncoder()
17	0.747	0.726	0.769	6.000	0.000	1,750.000	4.000	0.500	1.000	0.744	0.001	1.000	SimpleImputer(strategy='most_frequent')	OneHotEncoder()
18	0.747	0.729	0.764	1.000	0.000	147.000	1.000	0.500	0.500	0.500	0.000	2.230	SimpleImputer(strategy='most_frequent')	CustomOrdinalEncoder()
19	0.746	0.720	0.772	1.000	0.500	2,000.000	1.000	1.000	1.000	0.667	1.000	4.000	SimpleImputer(strategy='most_frequent')	CustomOrdinalEncoder()
20	0.746	0.715	0.777	17.000	0.000	100.000	5.000	0.500	0.938	0.941	0.000	1.000	SimpleImputer(strategy='median')	OneHotEncoder()
21	0.746	0.725	0.766	2.000	0.077	617.000	1.000	0.652	0.776	0.500	0.269	1.000	SimpleImputer()	CustomOrdinalEncoder()
22	0.744	0.715	0.773	37.000	0.000	1,306.000	1.000	0.691	1.000	0.819	0.080	1.000	SimpleImputer()	CustomOrdinalEncoder()
23	0.744	0.714	0.773	1.000	0.038	2,000.000	10.000	0.500	0.500	0.559	1.000	1.000	SimpleImputer(strategy='most_frequent')	CustomOrdinalEncoder()
24	0.742	0.724	0.761	1.000	0.000	2,000.000	2.000	0.500	0.881	0.500	0.000	1.000	SimpleImputer(strategy='most_frequent')	CustomOrdinalEncoder()
25	0.742	0.705	0.778	2.000	0.000	136.000	2.000	0.500	0.796	0.657	0.000	1.000	SimpleImputer(strategy='most_frequent')	OneHotEncoder()
26	0.737	0.720	0.753	18.000	0.500	249.000	1.000	1.000	1.000	0.672	0.391	4.000	SimpleImputer(strategy='most_frequent')	CustomOrdinalEncoder()
27	0.736	0.716	0.756	3.000	0.000	1,450.000	4.000	0.988	0.754	0.945	0.000	1.000	SimpleImputer(strategy='median')	CustomOrdinalEncoder()
28	0.732	0.698	0.766	1.000	0.000	100.000	1.000	0.500	1.000	0.552	0.329	1.705	SimpleImputer(strategy='most_frequent')	CustomOrdinalEncoder()
29	0.729	0.710	0.748	1.000	0.000	2,000.000	2.000	0.500	1.000	0.500	0.000	3.531	SimpleImputer(strategy='median')	OneHotEncoder()
30	0.728	0.709	0.747	2.000	0.186	261.000	12.000	0.820	0.973	0.738	0.091	1.706	SimpleImputer(strategy='median')	CustomOrdinalEncoder()
31	0.727	0.691	0.763	1.000	0.449	242.000	3.000	0.787	0.918	0.691	0.030	2.709	SimpleImputer()	CustomOrdinalEncoder()
32	0.726	0.684	0.768	1.000	0.000	119.000	1.000	0.864	0.552	0.641	0.000	1.385	SimpleImputer(strategy='most_frequent')	CustomOrdinalEncoder()
33	0.726	0.700	0.751	9.000	0.135	171.000	3.000	0.500	1.000	0.898	0.834	4.000	SimpleImputer(strategy='median')	OneHotEncoder()
34	0.724	0.706	0.743	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	OneHotEncoder()
35	0.724	0.697	0.751	2.000	0.500	126.000	1.000	0.931	1.000	0.714	0.476	1.341	SimpleImputer()	CustomOrdinalEncoder()
36	0.721	0.684	0.758	3.000	0.068	1,485.000	2.000	0.500	0.500	0.885	0.141	4.000	SimpleImputer()	OneHotEncoder()
37	0.721	0.704	0.738	50.000	0.085	2,000.000	1.000	0.500	0.500	1.000	1.000	1.291	SimpleImputer()	CustomOrdinalEncoder()
38	0.719	0.696	0.743	19.000	0.089	429.000	10.000	0.736	0.878	0.550	0.002	1.131	SimpleImputer(strategy='median')	OneHotEncoder()
39	0.718	0.687	0.750	36.000	0.073	1,465.000	2.000	0.653	0.785	0.588	0.325	2.062	SimpleImputer(strategy='median')	CustomOrdinalEncoder()
40	0.718	0.701	0.734	21.000	0.235	135.000	2.000	0.689	0.824	0.979	0.032	1.872	SimpleImputer(strategy='median')	CustomOrdinalEncoder()
41	0.717	0.689	0.745	8.000	0.500	472.000	1.000	0.500	0.500	0.781	0.032	1.371	SimpleImputer(strategy='median')	CustomOrdinalEncoder()
42	0.712	0.698	0.725	32.000	0.483	281.000	2.000	0.843	0.699	0.784	0.000	1.000	SimpleImputer(strategy='median')	OneHotEncoder()
43	0.711	0.693	0.729	7.000	0.278	1,692.000	4.000	0.936	0.805	0.688	0.000	1.674	SimpleImputer(strategy='median')	CustomOrdinalEncoder()
44	0.701	0.674	0.729	10.000	0.395	131.000	3.000	0.500	1.000	0.873	1.000	1.000	SimpleImputer(strategy='median')	CustomOrdinalEncoder()
45	0.700	0.666	0.735	17.000	0.221	400.000	2.000	0.500	1.000	0.822	0.045	1.000	SimpleImputer()	CustomOrdinalEncoder()
46	0.699	0.666	0.732	6.000	0.153	1,510.000	10.000	0.873	0.543	0.701	0.853	1.133	SimpleImputer(strategy='median')	OneHotEncoder()
47	0.698	0.665	0.731	33.000	0.372	923.000	20.000	0.968	0.850	0.978	0.022	2.465	SimpleImputer(strategy='median')	OneHotEncoder()
48	0.698	0.670	0.725	3.000	0.000	385.000	50.000	0.985	1.000	0.611	0.082	4.000	SimpleImputer()	OneHotEncoder()
49	0.695	0.671	0.719	5.000	0.402	2,000.000	28.000	0.500	0.858	1.000	1.000	1.000	SimpleImputer()	CustomOrdinalEncoder()
50	0.684	0.651	0.718	3.000	0.457	226.000	7.000	0.648	0.646	0.774	0.000	2.574	SimpleImputer()	CustomOrdinalEncoder()

results.to_formatted_dataframe(query='model == "LogisticRegression()"', num_rows=60, include_rank=True)

rank	roc_auc Mean	roc_auc 95CI.LO	roc_auc 95CI.HI	C	imputer	scaler	encoder
1	0.777	0.756	0.798	0.101	SimpleImputer()	StandardScaler()	OneHotEncoder()
2	0.774	0.761	0.787	0.046	SimpleImputer()	StandardScaler()	OneHotEncoder()
3	0.771	0.744	0.798	<NA>	SimpleImputer()	StandardScaler()	OneHotEncoder()
4	0.771	0.737	0.805	0.188	SimpleImputer(strategy='most_frequent')	StandardScaler()	OneHotEncoder()
5	0.771	0.747	0.794	0.175	SimpleImputer()	StandardScaler()	OneHotEncoder()
6	0.770	0.744	0.795	0.160	SimpleImputer(strategy='most_frequent')	StandardScaler()	OneHotEncoder()
7	0.769	0.744	0.795	0.110	SimpleImputer()	StandardScaler()	OneHotEncoder()
8	0.769	0.747	0.791	0.259	SimpleImputer(strategy='most_frequent')	StandardScaler()	OneHotEncoder()
9	0.769	0.730	0.808	0.425	SimpleImputer(strategy='most_frequent')	StandardScaler()	OneHotEncoder()
10	0.769	0.737	0.801	0.017	SimpleImputer(strategy='most_frequent')	MinMaxScaler()	OneHotEncoder()
11	0.769	0.747	0.791	0.050	SimpleImputer()	MinMaxScaler()	OneHotEncoder()
12	0.769	0.755	0.782	0.204	SimpleImputer()	StandardScaler()	OneHotEncoder()
13	0.768	0.740	0.796	0.018	SimpleImputer(strategy='most_frequent')	MinMaxScaler()	OneHotEncoder()
14	0.767	0.740	0.795	0.777	SimpleImputer(strategy='most_frequent')	StandardScaler()	OneHotEncoder()
15	0.765	0.734	0.797	3.026	SimpleImputer()	StandardScaler()	OneHotEncoder()
16	0.764	0.741	0.788	0.245	SimpleImputer(strategy='most_frequent')	StandardScaler()	OneHotEncoder()
17	0.763	0.740	0.787	0.054	SimpleImputer(strategy='most_frequent')	MinMaxScaler()	OneHotEncoder()
18	0.763	0.739	0.788	1.076	SimpleImputer()	MinMaxScaler()	OneHotEncoder()
19	0.763	0.739	0.787	0.249	SimpleImputer(strategy='most_frequent')	StandardScaler()	OneHotEncoder()
20	0.762	0.744	0.781	0.442	SimpleImputer()	StandardScaler()	OneHotEncoder()
21	0.761	0.734	0.789	38.539	SimpleImputer()	StandardScaler()	OneHotEncoder()
22	0.761	0.729	0.793	0.167	SimpleImputer()	StandardScaler()	OneHotEncoder()
23	0.761	0.744	0.778	0.000	SimpleImputer(strategy='most_frequent')	MinMaxScaler()	OneHotEncoder()
24	0.760	0.732	0.787	0.512	SimpleImputer(strategy='most_frequent')	StandardScaler()	OneHotEncoder()
25	0.759	0.735	0.783	0.270	SimpleImputer(strategy='most_frequent')	MinMaxScaler()	OneHotEncoder()
26	0.759	0.735	0.782	0.000	SimpleImputer(strategy='median')	MinMaxScaler()	OneHotEncoder()
27	0.758	0.726	0.791	0.029	SimpleImputer(strategy='most_frequent')	MinMaxScaler()	OneHotEncoder()
28	0.758	0.729	0.787	0.001	SimpleImputer()	MinMaxScaler()	OneHotEncoder()
29	0.758	0.729	0.786	0.000	SimpleImputer(strategy='median')	MinMaxScaler()	OneHotEncoder()
30	0.756	0.734	0.778	100.000	SimpleImputer(strategy='most_frequent')	MinMaxScaler()	OneHotEncoder()
31	0.756	0.732	0.781	4.069	SimpleImputer(strategy='most_frequent')	StandardScaler()	OneHotEncoder()
32	0.756	0.741	0.771	100.000	SimpleImputer(strategy='most_frequent')	StandardScaler()	OneHotEncoder()
33	0.756	0.709	0.802	0.000	SimpleImputer(strategy='most_frequent')	MinMaxScaler()	OneHotEncoder()
34	0.754	0.724	0.784	0.001	SimpleImputer(strategy='most_frequent')	MinMaxScaler()	OneHotEncoder()
35	0.752	0.724	0.780	0.000	SimpleImputer()	MinMaxScaler()	OneHotEncoder()
36	0.751	0.720	0.782	0.003	SimpleImputer(strategy='most_frequent')	StandardScaler()	OneHotEncoder()
37	0.751	0.721	0.780	100.000	SimpleImputer()	MinMaxScaler()	OneHotEncoder()
38	0.751	0.730	0.772	0.000	SimpleImputer()	MinMaxScaler()	OneHotEncoder()
39	0.749	0.719	0.780	2.387	SimpleImputer(strategy='most_frequent')	MinMaxScaler()	OneHotEncoder()
40	0.744	0.712	0.776	0.002	SimpleImputer()	StandardScaler()	OneHotEncoder()
41	0.743	0.720	0.766	100.000	SimpleImputer()	StandardScaler()	OneHotEncoder()
42	0.734	0.703	0.764	0.000	SimpleImputer()	StandardScaler()	OneHotEncoder()
43	0.733	0.710	0.756	0.560	SimpleImputer()	StandardScaler()	CustomOrdinalEncoder()
44	0.732	0.705	0.760	0.003	SimpleImputer()	StandardScaler()	CustomOrdinalEncoder()
45	0.732	0.701	0.763	30.308	SimpleImputer(strategy='median')	MinMaxScaler()	CustomOrdinalEncoder()
46	0.730	0.710	0.749	0.000	SimpleImputer(strategy='most_frequent')	StandardScaler()	OneHotEncoder()
47	0.729	0.701	0.757	96.799	SimpleImputer(strategy='most_frequent')	StandardScaler()	CustomOrdinalEncoder()
48	0.729	0.712	0.746	1.452	SimpleImputer(strategy='median')	MinMaxScaler()	CustomOrdinalEncoder()
49	0.725	0.706	0.743	0.000	SimpleImputer(strategy='median')	StandardScaler()	CustomOrdinalEncoder()
50	0.708	0.672	0.745	0.004	SimpleImputer(strategy='most_frequent')	MinMaxScaler()	CustomOrdinalEncoder()
51	0.705	0.681	0.729	0.000	SimpleImputer(strategy='median')	MinMaxScaler()	CustomOrdinalEncoder()

BayesSearchCV Performance Over Time

results.plot_performance_across_trials(facet_by='model').show()

results.plot_performance_across_trials(query='model == "XGBClassifier()"').show()

---

Variable Performance Over Time

results.plot_parameter_values_across_trials(query='model == "XGBClassifier()"').show()

---

Scatter Matrix

# results.plot_scatter_matrix(query='model == "XGBClassifier()"',
#                             height=1000, width=1000).show()

---

Variable Performance - Numeric

results.plot_performance_numeric_params(query='model == "XGBClassifier()"',
                                        height=800)

results.plot_parallel_coordinates(query='model == "XGBClassifier()"').show()

---

Variable Performance - Non-Numeric

results.plot_performance_non_numeric_params(query='model == "XGBClassifier()"').show()

---

results.plot_score_vs_parameter(
    query='model == "XGBClassifier()"',
    parameter='learning_rate',
    size='colsample_bytree',
    color='encoder',
)

---

results.plot_parameter_vs_parameter(
    query='model == "XGBClassifier()"',
    parameter_x='colsample_bytree',
    parameter_y='learning_rate',
    size='max_depth'
)

results.plot_parameter_vs_parameter(
    query='model == "XGBClassifier()"',
    parameter_x='colsample_bytree',
    parameter_y='learning_rate',
    size='imputer'
)